Computational modeling for predicting the drug metabolism: A novel approach for developing new drugs and to predict drug interactions

Abstract

Drug metabolism (DM) plays the crucial role in the drug therapy and research as it influences the pharmacokinetics (PK), Pharmacodynamic (PD) of the drug, decides the drug’s efficacy and safety and drug interactions (DDIs). An exogenous compound includes the drugs, toxins and other foreign materials undergoes metabolism. The current review represents the computational approaches to predict the drug metabolism in human. This explains the metabolism related aspects for a drug molecule related to the type of enzyme that metabolise, binding sites on the substrate, metabolites formation process and drug-drug interactions. As the usage of multiple drugs containing regimens is increased, the identification and prediction of drug interactions is gaining importance in the personalized medication. The present review also exemplified using a case study by using the propionic derivatives drugs metabolism prediction by using in silico software’s Bio Transformer 3 and AutoDock vina against enzymes Cytochrome P 450 and transferase enzymes. The binding score obtained for the above molecules and enzymes guiding safer and more effective drug design. Finally, based on the study concluded that every drug had their individual enzyme and metabolism process even though they are structurally similar.